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1 2021 Chantry, M. et al.: "Machine Learning Emulation of Gravity Wave Drag in Numerical Weather Forecasting". Journal of Advances in Modeling Earth Systems, 13, e2021MS002477. https://doi.org/10.1029/2021MS002477
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2 2021 Sonnewald, et al.: "Bridging observations, theory and numerical simulation of the ocean using machine learning". Environ. Res. Lett. 16 073008
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3 2021 Hatfield, et al.: "Building Tangent-Linear and Adjoint Models for Data Assimilation With Neural Networks". Journal of Advances in Modeling Earth Systems, 13, e2021MS002521
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4 2021 Agarwal et al.: "A Comparison of Data-Driven Approaches to Build Low-Dimensional Ocean Models". Journal of Advances in Modeling Earth Systems, 13, e2021MS002537
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5 2021 Kloewer et al.: "Compressing atmospheric data into its real information content". Nat Comput Sci 1, 713–724 (2021). https://doi.org/10.1038/s43588-021-00156-2
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6 2022 Rausch, Ben-Nun et al.: "A Data-centric Optimization Framework for Machine Learning". Proceedings of the 36th ACM International Conference on Supercomputing Download PDF
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7 2022 Gong B, Langguth M, Ji Y, Mozaffari A, Stadtler S, Mache K, Schultz MG.: "Temperature forecasting by deep learning methods". EGU Geoscientific Model Development
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8 2022 Dueben et al.: "Benchmark Datasets for Machine Learning in the Atmospheric Sciences: Definition, Status, and Outlook". Artificial Intelligence for the Earth Systems, 1(3), e210002. Retrieved Sep 1, 2022
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9 2022 Ashkboos et al.: "ENS-10: A Dataset For Post-Processing Ensemble Weather Forecast". arXiv preprint arXiv:2206.14786
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10 2022 David Meyer et al.: "Machine learning emulation of urban land surface processes". Journal of Advances in Modeling Earth Systems, 14, e2021MS002744
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11 2022 David Meyer et al.: "Machine Learning Emulation of 3D Cloud Radiative Effects". Journal of Advances in Modeling Earth Systems, 14, e2021MS002550
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12 2022 Patrick Laloyaux et al.: "Deep learning to estimate model biases in an operational NWP assimilation system". Journal of Advances in Modeling Earth Systems, 14, e2022MS003016
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13 2022 Lorenzo Pacchiardi et al.: "Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization". arXiv preprint arXiv:2112.08217
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14 2021 Nikoli Dryden et al.: "Clairvoyant Prefetching for Distributed Machine Learning I/O". Supercomputing
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15 2021 Shigang Li and Torsten Hoefler: "Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines". Supercomputing
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16 2022 Shigang Li and Torsten Hoefler: "Near-Optimal Sparse Allreduce for Distributed Deep Learning". PPoPP
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17 2021 Chris Cummins et al.: "ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations". International Conference on Learning Representations (ICLR)
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18 2022 Bryan Plummer et al.: "Neural Parameter Allocation Search". International Conference on Learning Representations (ICLR)
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19 2022 Tal Ben-Nun et al. : "Productive Performance Engineering for Weather and Climate Modeling with Python". Supercomputing
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20 2022 Saleh Ashkboos et al.: "A Dataset For Post-Processing Ensemble Weather Forecast". Proceedings of the Neural Information Processing (NeurIPS) Systems Track on Datasets and Benchmarks
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